Which are the main applications of edge preserving filters?
Edge-preserving filters find applications in various fields such as image processing, computer vision, and graphics. The main applications of edge-preserving filters include image smoothing, denoising, enhancement, structure-preserving texture removal, mutual-structure extraction, HDR tone mapping, stereo matching, optical flow, joint depth map upsampling, edges detection, image abstraction, texture editing . Additionally, these filters are utilized in image matting/feathering, dehazing, detail enhancement, HDR compression, joint upsampling, and more in computer vision and computer graphics applications . Furthermore, edge-preserving filters play a crucial role in diverse applications like learning filter parameters from data, image segmentation tasks, and incorporating bilateral filters in CNNs for high-dimensional sparse data processing . The versatility and effectiveness of edge-preserving filters make them essential tools in various image processing and computer vision tasks.
Answers from top 5 papers
Papers (5) | Insight |
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03 Apr 2020 | Main applications of edge-preserving filters include image smoothing for preserving salient edges and structure-preserving smoothing for preserving salient structures, as discussed in the paper. |
Main applications of edge-preserving filters include edge-aware smoothing, detail enhancement, HDR compression, image matting/feathering, dehazing, and joint upsampling in computer vision and graphics. | |
Edge preserving filters are crucial in image smoothing, denoising, enhancement, structure-preserving texture-removing, mutual-structure extraction, HDR tone mapping, colorization, and more in computer vision applications. | |
01 Jun 2016 | Edge-preserving filters are used in image filtering, dense CRFs for image segmentation, and in bilateral neural networks for high-dimensional sparse data processing, as highlighted in the paper. |
07 Dec 2015 | Main applications of edge-preserving filters include stereo matching, optical flow, joint depth map upsampling, edge-preserving smoothing, edges detection, image abstraction, and texture editing as demonstrated in the paper. |